Walkthroughs, demos, and deep dives. Our notes first, the original next.
Integrations
10 videos
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CodeWithChris explains TypeSafe AI's Jev model, framing it as an AI decision engine rather than a text generator. He then builds a step-by-step Zapier automation that ingests Crisp support tickets, queries Jev with custom IDs and confidence thresholds, and alerts Slack for urgent issues.
Duration: 14 minutes 24 seconds. View notes : What Is Jev? How It Works + Full TutorialMore walkthroughs, examples, and different perspectives.
Stephanie Nyarko demonstrates how to integrate Jev into an n8n workflow via OpenRouter HTTP requests. She configures Gmail email triage across multi-question decision categories, uses confidence scores to trigger human review, and explains limitations.
Duration: 18 minutes 42 seconds.Corbin explains Jev's primitive outputs like choice and score, demonstrating how to build a Next Gen Zap via Cursor to triage Gmail messages by category.
Duration: 8 minutes 6 seconds.This video breaks down TypeSafe AI's Jev model, explaining its three typed primitives (Noul, Choice, Score) and confidence computation. It details six LLM system integration patterns—including routing, RAG filtering, guardrails, and verification cascades—alongside critical failure modes like distribution shifts and semantic divergences between Choice and Noul queries.
Duration: 9 minutes 15 seconds.This tutorial teaches how to integrate TypeSafe Jev into Zapier workflows to replace costly LLM prompts for email categorization, explaining structured fields, confidence thresholds, and downstream routing.
Duration: 13 minutes 17 seconds.This video introduces TypeSafe's Jev model, explaining how fast decision models differ from text-generating LLMs. It reviews practical use cases like ad classification and inbox triaging, and demonstrates integrating Jev with Zapier via Claude prompts.
Duration: 13 minutes 44 seconds.This Portuguese-language tutorial demonstrates integrating Jev alongside DeepSeek to audit legal contracts. It covers sequential question-by-question API calls, confidence cutoff thresholds for manual review, and user-configurable risk checklists.
Duration: 21 minutes 28 seconds.Luís demonstrates evaluating marketing leads in n8n using Jev compared to traditional LLMs. He explains Jev's structured choice, score, and probability outputs, illustrating how CRM event histories can be classified with low latency and favorable per-request economics.
Duration: 41 minutes 29 seconds.This video demonstrates using TypeSafe AI's Jev model with WebRTC and Deepgram to provide real-time decision-making and compliance guidance for human customer service agents.
Duration: 5 minutes 14 seconds.Jeremy Chone live-codes an ergonomic Rust library for TypeSafe AI's Jev model, inspecting its API request structure, typed criteria, probability outputs, and architectural trade-offs.
Duration: 164 minutes 40 seconds.
